1. Why Exporting Matters Jaap Bos Maastricht University Claire Economidou Univesrity of Pireaus Mark Sanders Utrecht School of Economics m.w.j.l.sanders@uu.nl 31 October 2013 Utrecht

2. Motivation  It is relatively well established in the literature that export orientation leads to better economic performance.  At the aggregate country level: e.g. Edwards, 1998; Bhagwati, 1998; Frankel and Romer, 1999  At the firm level: e.g. Chen and Tang, 1987;Aw and Hwang 1995, Bernard and Jensen, 1995, 2004; Girma et al., 2004; De Loecker, 2007.  For elaborate overviews: e.g. Greenaway and Kneller, 2007; Wagner, 2007, 2012.

3. Motivation  While productivity differences between exporters and non-exporters are well-documented in the literature:  less is known about the roots of these differences, and  the direction of causality is not settled yet: whether it is exports that cause better performance ("learning") or the other way around ("market selection").

4. Motivation On Learning vs. Selection Study:Country/Region:Confirms: Clerides et al. (1998)Mexico, Morrocco, ColumbiaSelf-selection Bernard and Jensen (1999) USA Self-selection Castellani (2002) Italy Learning Delgado et al. (2002) Spain Self-selection Girma et al. (2004) U.K.Self-selection Van Biesebroeck (2005) Sub-Saharan Learning countries De Loecker (2007)Slovenia Learning. Manjon (2013)SpainLearning Love and Ganotakis (2013)UK SMEsLearning Gupta et al. (2013)IndiaLearning. Etc.

5. Contributions  Discussion seems to focus on estimation techniques and developing countries:  Few have investigated an advanced small open economy.  We analyze a large Dutch panel of firms  Including both manufacturing and services firms  Few (Girma et al 2004) apply matching techniques to account for selection.  We find selection effects are big for entrants and quitters

6. Key Findings Nobody has questioned the “measurement” of productivity:  We estimate a stochastic production frontier  We decompose productivity growth in its components  We find that exporters realize more efficiency gains and benefit from scale (vs. non-exporters)  We find non-exporters are more innovative (vs. exporters)  We find that entrants do not gain efficiency (vs. non-exporters)  We find that quitters indeed lag in efficiency (vs. exporters) Few (post Clerides et al. 1998) theorized about underlying mechanisms:  We (will) develop new testable hypotheses on learning by exporting for future research, based on our results

7. The Storyline A X f(k) A N f(k) Y/L K/L A X >A N g A X =g A N g A E >g A N,X g A Q <g A N,X Results are mixed at best

8. Our Storyline Y/L K/L Y* ijt =T jt f(k ijt ) Y=E N ijt *T jt *f(k ijt ) Y=E X ijt *T jt *f(k ijt ) E X >E N g E X >g E N g T X <g T N g T E >g T N g E Q <g E X

9. Methodology Firms all produce under same frontier given by: Then a given firm produces at any given time: Where υ ijt measures inefficiency. Differentiating (2) w.r.t. time gives: (1) (2) (3)

10. Methodology Estimate (2) in translog: Decompose following Kumbahkar and Lovell 2004: (4)

11. Methodology

12. y ijt =b j + b always D always + b starter D starter + b quitter D quitter + b switcher D switcher + ε ijt y ijt is the productivity growth component (gTFP, TC, EC and ES) of firm i in industry j at time t. We include industry-specific fixed effects. Note: A straightforward interpretation of the results from equation above requires the assumption that firms are randomly selected to either export or not, otherwise the results may confound learning and selection. Therefore, we subsequently estimate the propensity to export.

13. Methodology D always =b 0 + b w w ijt + b size size ijt + b communication communication ijt + b j D j + ε ijt if D always = 1|D never = 1 where w is the price of labor; size is total assets; communication measures the amount of advertising and public relations expenditures of firms; and D j is a dummy for industry j, and is included for every industry except for the base industry. Note: For each type of exporter, we find the appropriate control group: starters are matched with firms that never export, quitters are matched with firms that always export, and switchers are matched with both firms that never export and firms that always export, respectively.

14. Exporting {1,0} As a next step, we repeat the estimation of equation above, but now estimate this equation for each group of exporters, respectively, for both TFP growth and its components. For example, for firms that always export, we estimate: gTFP ijt = b j + b always D always ijt + ε ijt if ps always > 0 (6) where ps always is the export propensity score from estimating equation (5). Hence, in estimating the equation above, we only include firms that always export and firms that never do, but have a similar propensity to export. We subsequently do the same for other groups of exporters (and their respective control groups).

15. Export Intensity To assess the marginal effect of exporting we estimate: gTFP ijt = b j + b expint expint ijt + b expint 2 expint 2 ijt + ε ijt if expint ijt > 0 (7) where expint ijt is the export intensity of firm i in industry j at time t, defined as exports over value added. As before, this equation has been estimated for both TFP growth and its components. To assess whether learning takes place, we consider δgTFP ijt /δexpint ijt, or b expint + 2 ∗ b expint 2 expint ijt, the marginal effect of export intensity on TFP growth. Depending on the sign for b expint 2, this effect is either in- or decreasing in export intensity.

16. Export Duration ΔgTFP ijt = b j + b always D always + ε ijt if ps always > 0, ∀ t = 1,..., 11 (8) where as before, ps always > 0 ensures that we estimate the export premium, b always, comparing firms that always export with those that never export, but have a similar propensity to export. We estimate equation above for each time period t, where - in this case only - t reflects the time that has passed since a firm started to export. We focus on starters and switchers, and report the development of b always over time. If exporters learn from exporting, we expect a positive premium that increases over time.

17. Data  76,898 Dutch firms in manufacturing (15,287) and services (61,611).  27 manufacturing and 10 services industries, at the NACE2 level (SBI in Dutch).  Period 1994-2004.  Output (Y), Capital (K) and Labor (L) to construct the production frontier production set as well as export share, wages, total assets and communication for the matching analysis (to calculate the propensity to export) are retrieved from the Netherlands Central Bureau of Statistics (CBS) Production Statistics (CBSPS) database.  Y, K and L are constructed following the EU KLEMS methodology, at the firm-level.

18. Data manufacturing services

19. Results Does it Matter if you Export? Manufacturing, matched samples gTFP ES TC EC always never -0.005 * 0.001 *** -0.011 *** 0.005 *** starter never -0.006 -0.000-0.001 -0.005 ** quitter always -0.007 ** 0.001-0.004-0.003 ** switcher always 0.005 *** 0.0000.007 *** -0.002 * switcher never 0.004 0.001 *** -0.001 0.004 *** Manufacturing, without matching (relative to never) gTFP ES TC EC always-0.008 *** 0.001 *** -0.011 *** 0.002 starter0.005 0.001 * 0.001 0.003 * quitter-0.011 *** 0.002 *** -0.013 *** 0.000 switcher 0.001 0.001 *** -0.003 0.003 * Selection Effects Confirmed Exporters premium in EC Entrants penalty in EC Exporters penalty in TC

20. Results Does it Matter if you Export? Services, matched samples gTFP ES TC EC always never -0.025 *** 0.001 ** -0.030 *** 0.006 *** starter never -0.024 *** 0.000-0.021 *** -0.003 *** quitter always -0.038 *** 0.001 ** -0.031 *** -0.009 *** switcher always 0.034 *** 0.0010.038 *** -0.005 *** switcher never 0.001 ** -0.001 ** 0.000 0.002 ** Services, without matching (relative to never) gTFP ES TC EC always-0.025 *** -0.000-0.027 *** 0.003 * starter0.028 *** 0.001 0.026 *** 0.002 ** quitter-0.023 *** 0.002 *** -0.020 *** -0.004 *** switcher -0.002 -0.001 ** -0.002 0.001 Same pattern Entrants and quitters penalty in TC

21. Results Does it Matter How Much you Export? Manufacturing gTFP TC EC always-0.003 (−) -0.001** (+) -0.002 (−) starter-0.015 (+) -0.016 (+) 0.001** (−) quitter0.018 (−) 0.017(−) 0.001** (−) switcher0.001** (−) 0.001** (−) -0.001** (−) Services gTFP TC EC always 0.001 (−) 0.002** (−) -0.002** (−) starter 0.006 (−) 0.005 (−) -0.000** (−) quitter 0.025 (+) 0.021 (+) 0.004** (+) switcher 0.036 (−) 0.032 (−) 0.002** (−) Intensity helps starters and quitters Exporters switch sign TC manuf.-Serv.

22. Results starter never ManufacturingServices Effects fade quickly

23. Conclusions 1. Does it Matter if you Export? Yes it does, for scale economies and efficiency change: but growth premia are not positive for technical change! 2. Does it Matter How Much you Export? Yes it does, for efficiency change, for always (0,-), for starters (+/- ), for quitters (+/+) and for switchers (-/+). 3. Does it Matter How Long you Export? Not really: any effects tend to fade quickly, except for starters in services sectors...

24. Questions/Comments Are highly appreciated…